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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Genitourinary Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1491848

An MRI radiomics model for predicting a prostate-specific antigen response following abiraterone treatment in patients with metastatic castration-resistant prostate cancer

Provisionally accepted
YI WU YI WU 1Xiang Liu Xiang Liu 2*Shaoxian Chen Shaoxian Chen 1*Fen Fang Fen Fang 1Feng Shi Feng Shi 3Yuwei Xia Yuwei Xia 3Ze-Hong Yang Ze-Hong Yang 2Daiying Lin Daiying Lin 1*
  • 1 Shantou Central Hospital, Shantou, China
  • 2 Sun Yat-sen Memorial Hospital, Guangzhou, Guangdong Province, China
  • 3 Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, China

The final, formatted version of the article will be published soon.

    Objective: To establish a combined radiomics-clinical model for the early prediction of a prostatespecific antigen(PSA) response in patients with metastatic castration-resistant prostate cancer(mCRPC) after treatment with abiraterone acetate(AA).The data of a total of 60 mCRPC patients from two hospitals were retrospectively analysed and randomized into a training group(n=48) or a validation group(n=12). By extracting features from biparametric MRI, including T2-weighted imaging(T2WI), diffusion-weighted imaging(DWI), and apparent diffusion coefficient(ADC) maps, radiomics features from the training dataset were selected using least absolute shrinkage and selection operator(LASSO) regression.Four predictive models were developed to assess the efficacy of abiraterone in treating patients with mCRPC. The primary outcome variable was the PSA response following AA treatment. The performance of each model was evaluated using the area under the receiver operating characteristic curve(AUC). Univariate and multivariate analyses were performed using Cox regression to identify significant predictors of the efficacy of abiraterone treatment in patients with mCRPC.Results: The integrated model was constructed from seven radiomics features extracted from the T2WI, DWI, and ADC sequence images of the training data. This model demonstrated the highest AUC in both the training and validation cohorts, with values of 0.889 (95% CI, 0.764-0.961) and 0.875 (95% CI, 0.564-0.991). The Rad-score served as an independent predictor of the response to abiraterone treatment in patients with mCRPC (HR: 2.21, 95% CI: 1.01-4.44).The biparametric MRI-based radiomics model has the potential to predict the PSA response in patients with mCRPC following abiraterone treatment.The MRI-based radiomics model could be used to noninvasively identify the AA response in mCRPC patients, which is helpful for early clinical decision-making.

    Keywords: Neoplasms (Prostate), biparametric MRI, Radiomics model, abiraterone, metastatic castration-resistant prostate cancer

    Received: 05 Sep 2024; Accepted: 07 Jan 2025.

    Copyright: © 2025 WU, Liu, Chen, Fang, Shi, Xia, Yang and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Xiang Liu, Sun Yat-sen Memorial Hospital, Guangzhou, 510000, Guangdong Province, China
    Shaoxian Chen, Shantou Central Hospital, Shantou, China
    Daiying Lin, Shantou Central Hospital, Shantou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.